{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as py\n",
    "import seaborn as sns\n",
    "%matplotlib inline\n",
    "plt.rcParams['font.sans-serif'] = 'SimHei'\n",
    "import re"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>user_id</th>\n",
       "      <th>item_id</th>\n",
       "      <th>behavior_type</th>\n",
       "      <th>user_geohash</th>\n",
       "      <th>item_category</th>\n",
       "      <th>time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>10001082</td>\n",
       "      <td>285259775</td>\n",
       "      <td>1</td>\n",
       "      <td>97lk14c</td>\n",
       "      <td>4076</td>\n",
       "      <td>2014-12-08 18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>10001082</td>\n",
       "      <td>4368907</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5503</td>\n",
       "      <td>2014-12-12 12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>10001082</td>\n",
       "      <td>53616768</td>\n",
       "      <td>4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9762</td>\n",
       "      <td>2014-12-02 15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>10001082</td>\n",
       "      <td>9947871</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2825</td>\n",
       "      <td>2014-11-28 20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>10001082</td>\n",
       "      <td>150720867</td>\n",
       "      <td>1</td>\n",
       "      <td>95qoghe</td>\n",
       "      <td>3200</td>\n",
       "      <td>2014-12-15 08</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    user_id    item_id  behavior_type user_geohash  item_category  \\\n",
       "0  10001082  285259775              1      97lk14c           4076   \n",
       "1  10001082    4368907              1          NaN           5503   \n",
       "2  10001082   53616768              4          NaN           9762   \n",
       "3  10001082    9947871              1          NaN           2825   \n",
       "4  10001082  150720867              1      95qoghe           3200   \n",
       "\n",
       "            time  \n",
       "0  2014-12-08 18  \n",
       "1  2014-12-12 12  \n",
       "2  2014-12-02 15  \n",
       "3  2014-11-28 20  \n",
       "4  2014-12-15 08  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_excel('data.xlsx')\n",
    "\n",
    "data.head()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 300105 entries, 0 to 300104\n",
      "Data columns (total 6 columns):\n",
      " #   Column         Non-Null Count   Dtype \n",
      "---  ------         --------------   ----- \n",
      " 0   user_id        300105 non-null  int64 \n",
      " 1   item_id        300105 non-null  int64 \n",
      " 2   behavior_type  300105 non-null  int64 \n",
      " 3   user_geohash   137505 non-null  object\n",
      " 4   item_category  300105 non-null  int64 \n",
      " 5   time           300105 non-null  object\n",
      "dtypes: int64(4), object(2)\n",
      "memory usage: 13.7+ MB\n"
     ]
    }
   ],
   "source": [
    "data.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>user_id</th>\n",
       "      <th>item_id</th>\n",
       "      <th>behavior_type</th>\n",
       "      <th>user_geohash</th>\n",
       "      <th>item_category</th>\n",
       "      <th>time</th>\n",
       "      <th>hour</th>\n",
       "      <th>date</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>10001082</td>\n",
       "      <td>285259775</td>\n",
       "      <td>1</td>\n",
       "      <td>97lk14c</td>\n",
       "      <td>4076</td>\n",
       "      <td>2014-12-08 18</td>\n",
       "      <td>18</td>\n",
       "      <td>2014-12-08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>10001082</td>\n",
       "      <td>4368907</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5503</td>\n",
       "      <td>2014-12-12 12</td>\n",
       "      <td>12</td>\n",
       "      <td>2014-12-12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>10001082</td>\n",
       "      <td>53616768</td>\n",
       "      <td>4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9762</td>\n",
       "      <td>2014-12-02 15</td>\n",
       "      <td>15</td>\n",
       "      <td>2014-12-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>10001082</td>\n",
       "      <td>9947871</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2825</td>\n",
       "      <td>2014-11-28 20</td>\n",
       "      <td>20</td>\n",
       "      <td>2014-11-28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>10001082</td>\n",
       "      <td>150720867</td>\n",
       "      <td>1</td>\n",
       "      <td>95qoghe</td>\n",
       "      <td>3200</td>\n",
       "      <td>2014-12-15 08</td>\n",
       "      <td>08</td>\n",
       "      <td>2014-12-15</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    user_id    item_id  behavior_type user_geohash  item_category  \\\n",
       "0  10001082  285259775              1      97lk14c           4076   \n",
       "1  10001082    4368907              1          NaN           5503   \n",
       "2  10001082   53616768              4          NaN           9762   \n",
       "3  10001082    9947871              1          NaN           2825   \n",
       "4  10001082  150720867              1      95qoghe           3200   \n",
       "\n",
       "            time hour        date  \n",
       "0  2014-12-08 18   18  2014-12-08  \n",
       "1  2014-12-12 12   12  2014-12-12  \n",
       "2  2014-12-02 15   15  2014-12-02  \n",
       "3  2014-11-28 20   20  2014-11-28  \n",
       "4  2014-12-15 08   08  2014-12-15  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#拆分出来小时\n",
    "data['hour'] = data['time'].map(lambda s:re.compile(' ').split(s)[1])\n",
    "#拆分出来天\n",
    "data['date'] = data['time'].map(lambda s:re.compile(' ').split(s)[0])\n",
    "\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 300105 entries, 0 to 300104\n",
      "Data columns (total 8 columns):\n",
      " #   Column         Non-Null Count   Dtype         \n",
      "---  ------         --------------   -----         \n",
      " 0   user_id        300105 non-null  int64         \n",
      " 1   item_id        300105 non-null  int64         \n",
      " 2   behavior_type  300105 non-null  int64         \n",
      " 3   user_geohash   137505 non-null  object        \n",
      " 4   item_category  300105 non-null  int64         \n",
      " 5   time           300105 non-null  datetime64[ns]\n",
      " 6   hour           300105 non-null  object        \n",
      " 7   date           300105 non-null  object        \n",
      "dtypes: datetime64[ns](1), int64(4), object(3)\n",
      "memory usage: 18.3+ MB\n"
     ]
    }
   ],
   "source": [
    "data['time'] = pd.to_datetime(data['time'])\n",
    "data.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## PV Page View 页面刷新一次就计算一次\n",
    "## UV Unique Visitor 一个IP是一个访客"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'pv和uv的日线')"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#pv_daily记录每天用户操作次数\n",
    "#uv_daily记录每天上线的用户数量\n",
    "pv_daily=data.groupby('date')['user_id'].count().reset_index().rename(columns={'user_id':'pv'})\n",
    "uv_daily=data.groupby('date')['user_id'].apply(lambda x:x.drop_duplicates().count()).reset_index().rename(columns={'user_id':'uv'})\n",
    "fig,axes=plt.subplots(2,1,sharex=True)\n",
    "pv_daily.plot(x='date',y='pv',ax=axes[0])\n",
    "uv_daily.plot(x='date',y='uv',ax=axes[1])\n",
    "axes[0].set_title('pv和uv的日线')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'uv_hour')"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "pv_hour=data.groupby('hour')['user_id'].count().reset_index().rename(columns={'user_id':'pv'})\n",
    "uv_hour=data.groupby('hour')['user_id'].apply(lambda x:x.drop_duplicates().count()).reset_index().rename(columns={'user_id':'uv'})\n",
    "fig,axes=plt.subplots(2,1,sharex=True)\n",
    "pv_hour.plot(x='hour',y='pv',ax=axes[0])\n",
    "uv_hour.plot(x='hour',y='uv',ax=axes[1])\n",
    "axes[0].set_title('pv_hour')\n",
    "axes[0].set_title('uv_hour')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "data.to_excel(r'处理结果.xlsx', index = False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='hour', ylabel='total_pv'>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#不同类型用户的pv值在一天中的分布\n",
    "pv_detail=data.groupby(['behavior_type','hour'])['user_id'].count().reset_index().rename(columns={'user_id':'total_pv'})\n",
    "fig,axes=plt.subplots(2,1,sharex=True)\n",
    "sns.pointplot(x='hour',y='total_pv',hue='behavior_type',data=pv_detail,ax=axes[0])\n",
    "sns.pointplot(x='hour',y='total_pv',hue='behavior_type',data=pv_detail[pv_detail.behavior_type!=1],ax=axes[1])\n",
    "# axes[0].set_title('pv_different_behavior_type')\n",
    "# axes[1].set_title('pv_different_behavior_type_except1')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'daily_user_buy')"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 购买产品用户的购买次数分布\n",
    "data_user_buy=data[data.behavior_type==4].groupby('user_id')['behavior_type'].count()\n",
    "sns.distplot(data_user_buy,kde=False)\n",
    "plt.title('daily_user_buy')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'daily_ARPPU')"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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tkE/AD8BoIFSUTX8hqXUoHTN58dV0HPAZW6BCkSh+92oXAKDHM1HU7yX3s3VYzRmPc1jNGM+heZo7tnm5sjZ0ylTHTE7pJOKAz9gC9eThAQyMKyPkHo+/qN8r2362Uq7bHHp8wfjm5YmqY/10uDRzuqxlmYyx+emBV7vQWGHDmiYnut3FHuFn3u1Kyjml4w+iOil/Dyj9dKrKzJzSScIjfMYWoK5hP57rHMSHLlqMpS47ejx+CJHbxiO58AXVTtqa4Q2EVZ+Lxzezj47kclh5hJ+EAz5jC9ADr3bBQMAtFy7G4ppy+IIRjBSxZj3bfraSw2ZCJCowEUrVo3Emj39mHx2pxm7hXa+ScMBnbIEJhqP4Q3s3rlrTgKbKMrRUK30Pizlx68uhLBNQ10AtGhXw+EMzSjIll93CdfhJOOAz3XgDYfSPTc72aSx4jx/qw7AviI9uWQIA8YDfXcSJW1mWWW7OVpapvp/O2GQIkajIkNLhfjrJOOAz3fzrriN43717Z/s0FrwHXulCS3UZLm9V9qVoqS4HgKJW6ngDETisJhgMlPG4XDpmymCeLuDX2K0YmVD66TAFB3ymmyN94+jxTMDDo65Zc3zAi5dODOPDFy2JB9/KMjMqbKaip3SylWQCiLdPVtNATbZVSJfDd9ktEIL76STigM900+1WRpCd/eOzfCYL129f7YLJQPjg5sXTbm+pLi9qwPdm2e1KymWbw3RtFaR4ewUeYMRxwGe6mAxF0BfL33cOeGf5bBamyVAEf3y9B9eub0Sd0zrtvpbqsvgLcjH4suxnK01N2mYflXvinTJTr951ObiBWjIO+EwXvSMTkKXVx3iEPysee/MsRvwhfPSiJTPukyP8YtXi+wJh2C25BHwVI/w0nTIll115UeMR/hQO+EwXXbHRo8Vk4JTOLLn/lS6cU2vHxStcM+5bXFOGiVCkaMHRG4ioSunYLSYQQVU/HY8vCKvJgLI0lT9T/XQ44Esc8JkuZLrgkhUuHOvnlI7ejvSNYd9pDz6yZcmMRmNAYqVOcfL4Skon+6StwUBwWNT10xn2BeGyz2ycJlWXm+PHMQUHfKaL08N+2MwGbF1Ri2FfkLsY6uyBV7pgMRnwvvNbUt5f7Fp8byAMh01d6y61/XQ8vvSrbAHAZDSgutwMN+fw4zjgM110uf1YUlOOtkYnAKCTR/m68QfD+NPrvXjnhqa0AbLYq229WfazTaR21yu3P30fHYnbK0zHAZ/polsG/AYHAOD4AOfx9fLnA2cwHgjHV9am4rSZUVVuLsriq1AkimA4CoeKSVtA6afjVZnDT9UpM5HLbuWUTgIO+KzohBDocvuxuKYcjRU2OK0mHuHr6P5XutDW4MAFS6szHtdSXVaUEb7aPjqS2pSOO0OnTInbK0zHAZ8V3bAvCH8wgqU15SAitDY4uFJHJ2/2jOJgzyg+umVp2slNqaWqvCi1+Go7ZUpKSidzwA9FohibDGcd4dfYOeAn4oDPik6WZC5xKZUgbQ1OHOPFV7p44NXTKDMbcfP5zVmPlSN8rWvx5faGuY3wM+fwZSvnVLtdJXLZLfD4g4hEi9frv5RwwGdF1zUcC/g1SsBvbXDC7QtiiCt1imp8MoRH9p/BTZuaUGHLHBgBYHFNOQLhKIY0nuRUu72h5LRmT+m4fZn76Eg18X46PMoHOOAzHcgRvqz1lhO3nNYprof3n4E/GMFHtyxVdfxUpY62aR0Z8J05lGUGwspEbzrZOmVKLgevtk3EAZ8VXZfbj4YKK2yxFZFtDUppJi/AKh4hBO5/+TTWN1dgY0ulqsfIF+RujSduc5+0zd4T35OlrYLk4tW203DAZ0Una/CleqcVTpuJR/hF9GbvKI70jeMjF2WfrJWKPcJX00sHUNdPJz7CzzZpyw3UpuGAz4pOqcG3x78mImXilkf4RXPozBgA4LLWWtWPsVtNqLFbNC/N9OVYpSOPy1SLLztlVqmowwc4pSNxwGdFJdsiJ47wASWP3zkwXrTujAtdj8cPo4HQVGnL6XHFqMXPN6UzliGl4/YH4bSaYDFlDmHxfjqc0gHAAZ8VmVLmByxxlU27vbXeiRF/CINcqVMU3e4JLKqywWTM7U+8pboMPRrX4nsDEViMhqzBWVKT0snWR0cyGQ2oKjdzSieGAz4rKrmQZ+YInydui6nb48fi6vLsByZpqS5Hz8gEohrWravd3lCqULHr1bDKgA/w4qtEHPBZUcmSzMUpUjoAl2YWS7d7Iq+Av7i6DMFwVNM1Erl0ygQQPzZblY5LZcCvtVs5pROTNeATUSUR7SSi3UT0JyKa8b9MRCYi6iKiZ2IfG4pzuqzUdLn9KDMbUeeYvqVendOKyjIz99QpgolgBEPeQLzqJhfFKM30qtztSpIpnUwbmXt8oaxtFSQe4U9RM8L/KIC7hRA7APQBuC7FMRsB/FYIsT328aaWJ8lKlyzJTC4NVCp1HLzdYRH0jqR+V6VGMUoz1e5nK5mNBtjMhoy7XimN07KvHgaU0kzumKnIGvCFED8RQuyOfVkHYCDFYe8AcDMRvUBE9xOR+p8um9e6Y10yU2mN9dThSh1tdbuV0fnimtxH+M1F6Ivvy6EXvpSpJ/5EMIKJUER1Dp/76UxRncMnoosBVAshXk5x92sAtgkhLgUwAuCGFI+/g4jaiah9cHAw3/NlJUS2RU6esJXa6h0YnQhhcJwrKLQkd63KJ4dfbjGh1mHRdITvzXGEDyj9dMbSpHTiq2xVpnRcsX46I9xPR13AJ6IaAD8GcFuaQw4KIc7GPj8CoDX5ACHEfUKIzUKIzXV1dXmd7Gx66e1h7Dvtme3TKClDXqUt8pI0I01ZqcN5fG11u/2wmgyoc1qzH5xCc3W5xiP8SE5VOoCSx0+Xw1fbOE2q4X46cWombS0AHgTwdSHE6TSH/ZqINhGREcDNAA5oeI6zzuML4o5fteNrfzw426dSUpLbIidrjQd8zuNrqds9gebqMtUtFZK1VJdp2hdf65SO2sZpkqzm0boLaClSM8K/HcAFAL4Rq8D5JhHdlXTMPwP4NYD9AF4SQuzR9jRn10+ffRvjgTCOD3jRO1KcPT/no6kafHvK+2sdFlSXm3GMtzvUVM9IfjX4Ukt1GXo1qsUXQsAbDMOZc8BP3yJZbeM0yRXrp8MjfCDrT0EIcS+Ae7Mc0wGlUmfe6RudxC/2nsL5S6rwetcInuscxIcvSr83KJsy1RY5dUpH2f3KySkdjXW7J3Du4qq8H7+4uhyhiMDAeACNObZmSOYPRiCE+rYKUqaAr7ZxmiRfGNy82pYXXmXzwyePISoEfvih87Co0oZnj/KEs1pdbj8aK2zxtsiptMW2O+RKHW2MTYYwOhEqeIQPaFOamWsfHclhNadtnubxBWEgoKJMXVmmrNfnlA4H/IxODvnwYHs3PnLREiyuKce2VXV48fgQQpH0GzOwKV3D6St0pLYGJ8Ynw+gf49GXFrrTrGzOxdTiq8IDfq772UpOmwneQDhlKaXbH0RVuQVGg7o5CrPRgMoyM6d0wAE/o7t3d8JiNOALVypFR5e31mE8EMYbXSO6nYMQAn2jk7p9Py11ZajBl1rreeJWS7IGP59VtlJ8hO8ufL4q1/1spfhq2xSjfGWVrbrRveRy8GpbgAN+WofOjOLPB87gtkuXxcvbtq6shdFAeK5Tv7TOU0cGsPW7T+JoX2kFxHRtkZNxTx1t9RRQgy/ZzEbUOa2alGbmup+tVJFh1ytlla26/L3kslu4YyY44Kf1g8ePorLMjDsuXxG/rbLMjPOXVOFZHQP+/u4RRAWws+Ns9oPnEBkslqYpyZRcDitcdgt3zdRIj2cCDqsJVTmOgJO1VJehZ0S7HH6uKR1HhhG+2xdU3UdHqrFbuIEaOOCn9OpJN54+OojPbluByqSJoW1tdXizd1TTboKZyJH97rf6dfl+Wskll7yyXtkMhRWu2+1HSwE1+FJLdXk8PVQIXzD/HD6QukWy25/HCN9h5ZQOOODPIITAv+46gnqnFbduXTbj/m1t9QCA54/pM8o/NuCFgZQt60ppDUBXmj74qbQ1OHG8n3vqaKHbk33eRI2W6jKcGZkouP+MDNi5B/zUKR0hBDx5pnQ8/qCmff5LUUkF/EhU4PiAN/42sRiePjqA9tMefOmqVpRZZuYd1y2qgMtu0aU8czIUwalhH27cuAgAsKeERvmyLXKtI/sfZluDA+OBMM6W6OT0XCGEQLd7oqAJW2lxdTnCUYH+scJ+JvmWZaYb4Y8HwghHRc4Bv8ZuQVQAIxPpe+wvBCUV8Ped9uDqu5/Fq6fcRXn+aFTg+493YqmrHLdcuDjlMQYD4fK2Ojx3bKjoo4XjA14IAVy7rhEr6uwlldY5PZy6LXIq3GJBG25fEBOhSEETtlKLRl0zfYEwiIDyFIOnTOTK3OSALzcvzyeHDwDDC3xLzZIK+KsalcBw+OxYUZ7/zwfP4PDZMfztjjaYM+wFuq2tDm5fEB1nRotyHpIMgG0NDly9tgEvnxjGaImMUDK1RU7G2x1qQ25aolVKB0DBPXW8gQjsFlPOcwrONNsc5tpHR6qNNVBb6H3xSyrgV5aZ0VxVhsNntR8JhiJR3L27E6sbnbgplkJJ57LWWhCh6OWZnf1emI2EZbV2XLO2AeGowDNHU21HMLfItsjZKnSkGrsFtQ5LSfXUcfuCmAhGZvs0ppmaKC88pbOoSrsRfq4lmQBgMxtgMtCMHL7so6O2U6Y01V6BA35JWdNUUZQR/u9f68bpYT/+4dpVMGRZwedyWLGhubLo5Zmd/eM4p9YBs9GAcxdXo9ZhwZ7Dcz/gD3mV1IKaCVuptb54PXU6+8fxkf98WbPdtSJRgZt+/ALu+utbmjyfVuTK2BYNUjo2sxENFdaC2yt4g7l3ygSUPkup+unI0kq1fXQkF6d0AJRgwF/b5MSJQS8mQ9qNriaCEfzoyWO4YGk1rlxdr+ox29rq8HrXSFFTLJ3942iLpbGMBsJVqxvwzJEBBMNzu7VDLhU6UluDIzZnoe28SO/IBD7xs1ex9+1h/ObldN29c7PvtAe9IxN4rUhzSfnqdk+gutycc0VMOi0a9MX3BXLvlCk5Yu0VEk2N8HNbZyDfEXBKp8SsaapAVGg7wffLl05hYDyAr123WnWu8fK2OkSiAnuPD2l2Hol8gTB6PBNoq3fEb9uxtgHjgTBeOTlclO+plXz6ubQ2OOENhHFGw0odty+IT/zsFfgCYWxsqcTOjj5NJtrlIrjjA174g8WrGMtVj0YlmVJLdVnB/XS8k/mN8AHAaZ3ZE9/tC8FiNOT8osb9dBQlGfAB7SZuRydCuPeZt7F9VR0uWl6j+nHnLa6C02YqWlrn2ICS3pAjfAC4tLUWZWbjnK/WOT2cuS1yKm0aV+r4g2Hc9ovX0O2ZwH99cjNuv3Q5BsYDeL2rsF3LolGBXR19qCwzIyqAt84Up4AgHz2eCU0qdKSW6jKcHZ1EuIBmgd48Nj+RnLaZ2xx6fEFU2815LSxT2itwwC8pS2rKYbcYNZu4/c/nTmB0IoS/v2ZVTo8zGQ24dGUtnu0cLMqCoc4+WaEzFfBtZiMua63Fnrf65/QiJTVtkZPJnjpa5NlDkSg+95vXcbBnBD/+8HnYco4LV66uh8VkwF/fLKxFxYGeEZwdncRntyktNw72FLdSS61oVKDXM4EWDSZspcXV5YhEBfoKqMX3BXPfz1ZSdr1KqtLx595WQVLaK3AOv6QYDIRVjU68pcEIPxoV+NVLp3D9+kasb67M+fHb2upwdnQyPhrX0tH+cVhNhhl58B1rG3BmdBKH5tDIMlm32592W8N0qsotqHNaC564jUYF/uEPB/Bs5yD+v5s34Np1jQCU4HF5ax12FZjW2dXRB7OR8JGLlqChwoo3e+dGwO8fn0QwEtV4hK88VyF5/Hz2s5WUFslJVTp5rLKVuGNmCQZ8YKpSp9BR7okhL8Ymw6onapNd3qZsxl6MVbed/eNYWe+Y0fP7ytX1MBDwxBxO63S5s/fBT6WtwVHQCF8Ige88dhgP7z+Dv7+mDR9K2pnshg2NODs6if09I3k//86OPmxdUYvKcjM2NFfOmYCvRVvkZFosvio0pZNyhJ9nwK+xcz+dkg3445PhgnvLyL72+W4Ht6iqDG0NDjxXhL46nf3jWJWQzpFcDisuWFo9Z/P4atsip9Ja78SxAW/eI/CfPnsCP3vhJG7dugyfv2LljPuvXtsAs5Hw2MH80jqHzoyhy+3H9euVdw0bmqvw9qA37c5Meoq3RdZw0rapygai/BdfhSJRBMNROCyFBfzEgZ3bF8y5JFNy2ZUR/kLup1OyAR9AwXn8/d0jcFpNWFHnyH5wGtva6vDKCbem1Rqj/hD6xwLxlgPJdqxtwOGzY5psQac1ORrMb4TvhD8YyeuF/MH2bnxv1xG8a9Mi/NONa1NO6lXYzListQ47O/ryene4q6MPRgPhmliaaGNLJYQADs2BUb4c4TdXaTfCt5qMaHDa8h7h59tHR3LazIhEBSZiJdjhSBSjE6ECRvjcT6ckA/7qRieICq/UOdAzgo2LK7MutMpkW1s9gpEoXjmhXU22bBW8qjH1C9GOtUrAmYvN1LrcPgD5jTTjE7c5rrjd81Y/vv4/b+Ky1lr84AObMv48r1/fiN6RiZwnW4UQeKzjLLYsr4nnkOW8z1xI63R7/GiosOY0Ua7G4pqyvAcW8e0NbXnW4Sf10xmdCEEIoCbPXv8uB29mXpIB3241YWlNeUEBfzIUwZGz43mnc6TNy6pRZjZqWp451UMn9Qh/ea0dK+sd2H14Dgb84dwXXUlTTdTUT9y2n3Lj8w+8jvWLKvDTj10Aiynzr/SOtQ0wGQiP5bihzLEBL04M+uLpHACoc1rRVGmbGwHf7dd0wlYqZPFVvvvZSskdM+Wiq5pYX5xcueyxfjoLeCOUkgz4QOEtFjp6RxGOCpy7uLqg87CZjbh4hUvbgN83DrvFmPHt+Y61DXjlhHvONVPrck+g3KKuLXKyyjIzGiqsqmvx95324LZfvIbmqjL8960XqkodVJVbcMnKWjz25tmc0jo73+wDEeJVP9KG5kq8OQdKM3s82rRFTqbU4k8glEctfqEpneRtDt0+5d98c/jcT6fEA/5ptz/v3vj7u0cAAJsW516Omezy1lqcHPLh9LCv4OcClBFua4Mz4+KSHXO0mZqs0Ml3x6W2BmfWrplCCPz6pVP40H0voarcgl/dfhFcOYz6btjQiG73RE6lrTs7zmLz0mrUV9im3b6huRInhnwp917VSygSxdnRCU0nbKWW6jJEBdCXxwpob2wDc0cBZZnA1AhfBupc2ypIchAyxAG/9KxpqoAQwJE8N/d+o3sEzVVlqHfash+cxbZVSlmnVt0zO/vH4/nsdM5tqUKd0zrnyjNzaYucysp6padOukqKiWAEf/eHA/hfjxzCpStr8ecvXJpzs7AdaxthNBAeU7kI6+SQD0f6xnHd+qYZ921oUQYMHb2zty7i7MgkoqKwjcvTkc+ZT4uFQkf4jnQpnTwnbeVkr5tTOqVnTVNhvfEPdI8UnL+XlrnKsaSmHM92Ft5XZ8gbwLAvmDZ/LxkMhKvX1OPZo4MIhIvTpncyFMlpWb1si5xP/l5qa3BiIhRJmTfuGvbjvffuxZ/e6MVXrm7Fzz55ISrzmMCrsVuwdYVLdVpH9s65bn3jjPs2NMuAP3tpnXiXTA1X2UqFLL6SOXx73mWZ5tjzyJROfpufSGajARU2E0/alqLmqjJU2Ex5rbgd8gbQ45nQLOATEba11WHv20MFd7LMNmGb6Oo1DfAGwnhZwwohKRIVuPae53Dnwx2qHzPoDeTcFjlZukqdp48O4Kb/eAG9Hj/++5MX4itXtxVUXXX9+iacGvarKu3d1dGHTYurUs6puBxWNFeV4WCBAb+jdxQPv9Gb12PjzeqKMMJvrLTBQEBPHrX4Po0nbd2+IMotxoIqkVwOK6d0ShERYXWeE7f7YwuuNmkU8AGlHt8fjKD9dGHBV+avVzVmD/iXrFSaqRWjPPP5Y4M4PezHg+3dOK6ydUR3Hm2Rk62sn16pE40K3LOnMz45+5cvXoYr8lwZneiadQ0w0NToPZ1utx8He0anVeckUyZuRwo6n399/Cj+/g8H8pqT6vFMwGggNFUWnp5MZjEZ0FiRXy1+wSmd2DsD2UDN48u/j47ksls4pVOq1jZV4GjfeM4r5/Z3j8BooPjbcS1cvMIFs5EKrtY52j+OCpsJ9c7sk5A2sxGXt9Viz2Htm6k9tK8HlWVm2MxG/PDJY6oeE++Dn2MfnUSVZWY0VthwrH8co/4QPv2rdtyz5xhuPq8Zf/zc1oKeO1Gtw4oty134a5a0zuOH+gAgc8BvqcSpYX/eFVP+YBgvnxhGOCry2q+52+NHU6UNpgzbchaipSa/0szxQBgWkyFrqWw6BgPBYTVNVen4g/Fa+nzV2Bd2P52SDvhrmpSVmadzfLt5oGcEqxqcKMtxY+VM7FYTLlxWU3BfnWP941jVmLlCJ9GOtUp/GC0nDUf9ITzxVj9uPq8Zt25dhr8cPIOjKibHu4YnQFT4as/WBgdeOenGTf/xAp4/Noj//Z71+LcPbNL05wUAN2xswolBX8a6/50dfVjbVIGlLnvaY+TAId8Vty8eH46nAl96O/e9DopVgy+1VOe3+MoXyL9TpuS0meDVcoTvWNgtkks84OfeGz8aFdjfPYJzl1Rpfj7b2upwpG8c/Xm2kxVC4GjfeNqWCqnIZmq73+rL63um8ujBMwiGo3j/BS244/JzYLeYcM+ezqyPy6ctciptDU70jkwgGI7i95+5GB9/x9K8yzwzuXZdA4iQtlqnb3QS+057Mo7ugamAn28e/6kjA3BYTbhgaTVezGNDnW7PhCb72KbTUl2Os2OTOc9PFdIpU0psoOb2598pU6qxW+DxL9x+OtrshTZL2hqcMMRaLNywYWbJXCpKzXRYswnbRNtW1eFfdh7Bs52D+ODmxTk/fmA8gLHJcMqmaenU2C3YvKwGT7zVj7/Nsad/Og+1d2N1oxPrFlWAiHDbpcvxoyeP4dCZUaxblD4NVmhJpvTBzYsRCEfw5avaUKcitZWveqcNFy6rwc6Os/jqjrYZ98fTOVl+t6rtFrRUl+W14lYIZS3FpStrsW5RBe7e0xnb5ENdYJsMRTA4Hij6CF8I4OzoRMZ3Osm8gXDeFTqS02bGeKxKx+MLaZDDtyISFap68kSiAg/t60bviPJiFwhHYv8qTeHit0WiCEcEPrl1meo4NFtKeoRvMxtxTp0jpxG+XHBVjIC/qsGJhgpr3nl8mTZpzVKDn+yatQ040jeed1fDRJ394zjQM4r3X9ASH1XffulyVNhM+PfdmUf5p92+giZspVWNTtz1ng1FDfbSOzc0obPfi+Mp+vfs7DiL1noHVtZn/3lsbMlvxe3hs+M4OzqJK1fXY+tKF4QAXjqhPq0jc+vFKMmUFudZmqlFSkfJ4YcRCEfgDYRRk+eiK0nOAahJ69yzpxNf++Ob+NGTx/DfL5zEH9p7sKujD3uPD+FgzwhODvkw5A0iEIpiYDyALzzwOh49cKag8yu2kh7hA0pa5/XT6ret29/tgaPADpnpEBG2t9XjsY6zCIQjsJpyezsrSzJzGeEDyqrbu/56GLvf6sdtly7P6bHJHtrXA5OB8J7zmuO3VZaZccfl5+AHT3Qq6bAUL5aToQj6xwKaBHw9Xbe+Ed989BAee7MPX7pq6v99yBvAqyfd+MKVraqeZ0NzFR57sw8j/iCqchiFPh1bKb19dR2qyy2wW4x48fiQ6pGirMEv9ggfQM55fF8gnNP/RSpOmwndbj88sbYK+XbKlNS2V3jycD9+/NRxfOCCFnzvfRuzlgD7g2F86uev4Su/ewME4KZNiwo6z2LJOsInokoi2klEu4noT0SU8n+ciH5GRHuJ6E7tTzO9NU1KvnfUr65C4kD3KDa2VM7YWEQr129oxPhkGM/nsQirs38cLrslpzYBALDUZUdrvaPgHvnhSBT/83ovrlhdj9qkc7j1kuWoLjfj7jSjfBkMlmpURaOXhgobNi+tnpHHf+JQP6Iic3VOoqkFWLlNnj91ZAAbmitR77TBbDRgyzku7M1h4rYnjw3jc9VUaYPRQPEWzGp5A+G8O2VKTpsZY5PheIDOt4+ONNVALf3iq65hP776+/1Yt6gC//s961Wt9yi3mPDzT12IzUtr8JXf78df89xzodjUpHQ+CuBuIcQOAH0Arks+gIjeC8AohNgKYBERqRsWaSA+cduX/Q9tMhTB4bNjRUnnSJesrEV1uRl/OZj7W7uj/V5VC65S2bG2Aa+ecqt+4Uvl2c5BDHkD+MAFLTPuc1hN+My2FXiucxDtKUoHu3QIPMVy/YYmHOkbx4nBqWqdnR1nscxVjtUq1kMAiRO3I6q/r8cXxBtdnmnrCraucOHkkA9nVO4J0O2ZgMVkQF2eHSTVMBllLX5uI3xvIJz35idShU0pyyy0rYKULaUzGYrgs7/ZBwC496MX5FSAIIP++Uuq8KXfvYGdBe6fXAxZA74Q4idCiN2xL+sApOrWtR3Ag7HPnwJwafIBRHQHEbUTUfvgoHadJdfmUKlz6IzskFml2fdPZjYacN36Rux+qx+TIfUtD6JRgeOxksx8XLe+EZGowG9f68rr8YCSznHZLWkXNn3i4qWodVhSjvILaYs82+QofmeHMkk74g/ipbeHcf2GJtXVQZXlZix1leeUx3+2cxBRgWlbbF6yshYAVI/yu91+tFSXFbTqWA2lL36uOfxI3ouuJIfVhEA4Gq98KzTgy0nfVCkdIQS+8acOvHV2DPd86Ny81nzYrSb8/FMX4dzFVfjib9/Arg7tque0oHrSloguBlAthHg5xd12AHJd+BiAhuQDhBD3CSE2CyE219XV5XWyqdQ7raixW1QF/EK3NFTrxo2L4AtG8PQR9Z0se0cm4AtGcp6wlTa2VOHqNQ348ZPH8ioLdfuC2HO4H+85rxnmNAt4yi0mfG77Sux9e3hGvbhsi+wq8A9yNiyqKsN5S6riaZ3db/UjHBWq0znS+hz3uH3qyABqHRZsTFgAuKrBCZfdgr0qyzOVtsjFf5HNtS++EAK+YDjvTpmSbK8g30EWmsO3mAxw2kwpUzoPvNqFP77egy9d1YorV88IYao5rCb84lMXYkNLJb7wwOt44tDcCfqqAj4R1QD4MYDb0hziBSDLBBxqn1cLRIQ1TU5VPVH2d49gUaVtRotbrW1ZXoNahwV/ySGPJ3vH5Dphm+ifblyLUFTgXx47nPNjH93fi1BE4P0p0jmJPrplCRoqrLh799FpK1S7YhU6xaiX18MN65tw6MwYTg/7sKujD81VZTmvxN7YXIkezwQ8KipAwpEonu0cxLa2+mmjc4OBcPEKF158e0jV6ulujx+Li9AHP1lLdRn6xydVN+rzByMQIv+2CpJsoCbfQVaVFValAyirrJNTOge6R/DtR9/C5W11+PJVhWeknTYzfnnbRVjfXInPP/D6nNmDWs2krQVKuubrQojTaQ7bh6k0ziYApzQ5O5XWNFbgaP941s6OB3qKs+AqmclowPXrm/DkkX7VvVGO9in541wWXSVb4irHZ7etwMP7z+CVHEr7AOAP+3qwvrkiPieSjs1sxOevWInXTnnw/LGpUWiXRjX4s+X6Dcpo/sH2bjx/bAjXr2/M+cVLtkpWM8p/o3sEoxOhaekcaeuKWvSPBfD2YOb9FcYnQxjxh3T5f2+pLocQwJkRde8eC+2jI8kR/mm3H5VlZk3aRyS3V3D7gvjcb/ahzmnFD285V7OCjgqbGb+6/SKsbarA39y/D0/OgR3q1Pzv3Q7gAgDfIKJniOibRHRX0jEPA/g4Ed0N4IMA/qrtaWa2pqkCwXAUJ4fS/4EMewPodmvXITObGzc2YTIUxZMq0zrH+sfRWGFDZYEjmM9tW4HmqjJ889FDqlsbv3VmDIfOjOH952ce3Uu3XLgYiypt+LfdnRBCxNsiLy3hgN9SXY5NLZW477kTCEai8ReAXOSyx+1TRwZgMhAua6udcd8lK10AgL1vZ07ryKqZYpZkSotzLM0sdHtDSY7wTw/7Cs7fS4kBPxIV+PLv3sCQN4h7P3Z+wSmjZErQ34I1TRX43G9ezynNWwxqJm3vFUJUCyG2xz6+LYS4M+mYMSgTty8DuEIIoWtzcDkqzdQqeWrBVWFbGqp14bIaNFRY8ReVCzGO9o/nnb9PVGYx4n/duAZH+sZx/yvqJnAf2tcDs5Hw7nObsx8MwGoy4otXteJA9wiePjqAQW8Ak6GoZo3NZsv1G5oQigg0VFhxXh6/JxU2M5bX2nFQRefMp48MYPOy6vg2fomW1JSjuaosa5uFeA1+ERddSS01uS2+8sV3u9JmhD/kDaI6z83Lk9U6LBiKdcy8Z08nnj82hG+/ex02tlRp8vzJKsvM+PVtW9DW6MBnfr1vVnep0yzXLoTwCCEeFELoPkOxst4Bs5Ey5vFlh8z1zZlTFloxGAg3bGjCM52DWbe/i0QFjg94C8rfJ7p2XSMua63Fvz1xFEMZ6o0BIBiO4uH9vbh6TUNOo5v3X9CCxTVluHt3Zzy/WsopHUDJ4wPAdesa86562dBcmbUWv3dkAkf6xlOmcwBlXuqSlS68fMKNSIaeL/FVtjqM8BsrbCgzG1VPSns1TukAhVfoJD6Pxx/EnreUxVUf3NyCD12YeyuUXFSWm/Gb27dgZb0j730PtFDSrRUki8mAFVlaLOzvHkFbgxPlBdYF5+LGjYsQDEezTth0uf0IhKN51+AnIyJ886Z18Acj+P6uoxmPffroANy+YNbJ2mRmowFfurIVHb1j+K/nTwIozZLMREtc5fj5py7El6+e2VdHrQ3Nlegdmcj4Qivf1qcL+IBSnjk6EcJbGfbd7Xb7YbcYNRv5ZmI0ELavqsMTh/ozvghJWqd0AC0DvjWeylm3qAL//O71uhQbVJVb8Ns73oHvf2BT0b9XOvMi4ANKPX66gB+NCk23NFTr/CXKLknZqnXiu1zlWYOfysp6B26/dDl+394dT2el8tC+HtQ6rNjWlnup7M3nNeOcWjt2HerTpC3yXHDFqvqCAouaidunjwygpbosY3uPi1coefwXM+TxezzKRLlelVHXrW/EkDeAN7qytzKZmrQtrCwz8QVDq/y6LB02GQ346cdyW1xVqMoyc9qyZz3Mm4C/pqkCA+OBlPW1J4d9GJsM4zydAz4R4Z0bm/D8scGMK2A7ZdM0FU26cvHFq1pR77Tinx7pSNkOdsgbwNNHBvDe85vzqn4wGQ348tVKCZsWbZHnA6XDKNCRZgHWZCiCF98ewpWr6zMG6nqnDa31jox5/G63PjX40pWr62ExGlQtJtJqhG8xGWCNbaBSaFsFqbXBgXKLEffccm7JpyFzNa8CPoCUeXy5paEeJZnJbtyoTAQ+nmHxReeAFy3VZQXnO5M5rCZ8451rcLBnFA+2d8+4/+E3ehGOZq+9z+TGjYuwutGZ9wrh+cYpJ27TjPBfOjGMyVBU1TaNl6ysxWun3Clr34UQSg2+DhO2ktNmxiUrXdjZ0Zd1jYBWZZny+wLajfDXLarEm9+6VpOtMkvNPAr4SsBJldbZ3z0Cu8VYlA6Z2WxorsSSmnL8OUNvnc6+cc3y98netWkRLlpWg+/tOoIR/1TtsRACD+3rwaaWyoK+t9FA+P0dF+OHHzpPi9OdFzY2p2+V/PSRAdjMBlx8jivr82xd4cJkKBpfIZ7I4w/BH4zoOsIHlLRO78gEDmWYWwCUgE8ElGuwS1lFbOJWqxE+gKI1T5zr5k3AdzmsqHdaUwb8Az0j2NhSNSs/ZCLCjRubsPft4ZTpplAkihND+TdNU/P9v/3udRidCE3rgXPozBiO9I3j/Xls1JKsstxc8PqB+WR9cyX6xiYxMD59kZIQAk8dGcAlK2pVpb+2nOOCgVL31ZF7H+ixyjbRjrWNMBCypnW8gQgcFpMm8wuyUkfrGvmFaN4EfEBJ6yTX4sc7ZM5COke6ceMiRKICu1KkdU4N+RCKCLRpUIOfzpqmCnzi4mX4zcunceiMMvJ8aF8PLCYD3rVxbvbtLmWynrsjKa1zfMCLHs+E6lRCZZkZG1qqUvbVmarB13eEX2O3YMtyV8rf5US+QFizFKVssaxVlc5CNu8C/tuD3ml7bx46M4ZQpLgdMrOflxPn1Nnx5xSLsI7KCp0ijfClr+5oQ3W5Bd985BAmQxE8vL8X16xtQKUOJX0LjZy4fbNn+uDjqVg5Zi6540tWuLC/e2RGi474KttZmHS8bn0jjg+k3iVM8gbCBVfoSE6r8jvKAb9w8yzgOxGKKIuYJFmSqHeFTiIlrbMIr5x0YyCpk2VnvxcGgqpt9ApRWWbG165bjfbTHnz19/sx4g8VNFnL0rPHdlR7M6k3/lNHBrC60ZlT+eolK2sRjgq8enL6HgTdHj+qy80FV8Hk49p1StuJTGkdrwbbG0pOmwlGA8Vz+Sx/8yrgp+qNv797BE06dMjM5qaNTRACM3ZW6uwbx1KXXZeSxvdf0IJNi6uws6MPDRVWXNaqXZtqNt3G5kocTJi4HZ0Iof20J+fKkAuWVsNiMswoz9SrLXIqjZU2nLekKmNaR8uUzuZl1djWVleynVjnknkV8JfX2mExGaYF/NlYcJVKa4MTqxqcMxZhdQ6MFzV/n8hgIPzzu9aBSAn+C7VSQQ8bWioxMB6I703w/LFBRKIi4+raVGxmIy5YUo0XkyZue9z6lmQmu25dIzp6x+KTx8m8Ggb8Wy5cgv++9UJNnmuhm1cB32Q0YFWDM77d4bA3gC63f04EfECpyW8/7YlvXzcZiuDUkK/o+ftEmxZXYdeXL8cXVW7OzfIje+nL8synjwyissycV2rxkpUuHD47Fq/yikYFejwTunTJTEemddKtL1E2P+EUzFwzrwI+gPhmKEIIHIh1LZwzAT+2k71M65wY9CEqij9hm2xVo5NXxRbZ2kUVMBBwsHcU0ajAs50D2NZWl9eK5q2xbQ9fPqHk8QfGAwhGovEOlrNhWa0dqxud6QN+IMIBfw6ahwG/Am5fEAPjAezvGoGBpvqbzLbltXasW1SBP8fSOp06Vegw/ZVbTGitd6KjdxQHe0cx5A3mnM6RNjZXwmk1xfvqxEsyda7BT3bd+ka0n/bMWG8AaJvSYdqZlwEfUHrj7+8Z1b1DZjY3blyEA90j6Hb70dk/DpOBsLzWPtunxYpgfWzi9qkjAzAQ8mpQByipyi3n1MTr8eUmJLM1aStdv14pRHji0PRusMFwFMFwtOD9bJn25l/Ab4wF/DNjONA9gvNmccFVKjduVHqu/+XgWXT2j8cnmtn8s7GlEkPeAB5q78Z5S6oLWil68YpanBr2o3dkIl6D3zLLI/y2BgeW19pnpHW07KPDtDXvIk1luRnNVWXY1dGH0YnQnMnfS4tryrFpcRX+cvAMOvu9mrZEZnOLTCWeGZ3MO50jyW0PXzw+hG63H/VO66zPwxARrl3XiJfeHp7Wp0mrzU+Y9uZdwAeUiVvZj1yvLQ1zcdPGJhw6M4Yutx9t9Rzw56u1TRXx0tcrVhUW8Fc1OFHrsGDv8aFYl8y50db3uvWNCEcFnjw8tW2fL6hNa2SmvXka8JW0jt1iLPoK1nzcsKEp/vmqxrl3fkwbNrMRrfUONFXa4t1c80VEuHhFLfa+PYxu98SsT9hKm1oq0VRpw86EVbec0pm75nXA39BSOScXFy2qKsPmpco7j1au0JnX/unGtfju+zZqskr0khUuDIwH0Dsye6tsk8m0znPHBuOB3qvRBuZMe/M64M/FdI5026XLcd6SKiydI2/NWXFsXVmbd3VOskti9fgAZnWVbbLr1jciGI7imaODAKZG+Bzw5555GfCXucpx5zvX4GPvWDLbp5LWDRua8Ke/uSSvhThsYVpcUx6vzJnNVbbJLlxWA5fdEu+t453UZj9bpr15GW2ICJ++7Jw587aXMa1cskIZ5c+VSVtA2T3qmnUNeOpwPyZDEc32s2Xa458IYyXkY+9YiqgQWJRDi2U9XLuuEb99tRsvHh/iSds5bF6O8Bmbrza0VOL7H9g054oRtq6ohdNqwq6OPniDYVhMBpg5XTnn8E+EMVYwi8mAq9bUY/fhfoxNhDidM0dxwGeMaeK69Y0Y8YfwzNFBDvhzFAd8xpgmtrXVw2Y24OzoJOfv5ygO+IwxTZRZjNjeprSQ4E6ZcxMHfMaYZq5br+yExSP8uYkDPmNMM1esrofZSBzw5yj+qTDGNFNZZsa337Uey2rnzsIwNoUDPmNMUx/ZMndbmix0qlI6RNRARM9nuL+ZiHqI6JnYhzbdohhjjGkm6wifiKoB/BJApo1XtwD4jhDiXq1OjDHGmLbUjPAjAG4BMJbhmHcA+BsieomI/j3VAUR0BxG1E1H74OBgHqfKGGOsEFkDvhBiTAgxmuWwnQC2CiEuBtBGRBtTPM99QojNQojNdXWc8WGMMb1pVZa5VwgxHvv8CIBWjZ6XMcaYRrQK+I8TURMRlQO4FkCHRs/LGGNMIzmXZRLRlQDWCiH+I+HmbwN4GkAQwE+FEEc1Oj/GGGMaUR3whRDbY/8+BeCppPueBrBa0zNjjDGmKRJC6P9NiQYBnC7gKWoBDGl0OrNpvlwHwNcyF82X6wD4WqSlQoi8q15mJeAXiojahRCbZ/s8CjVfrgPga5mL5st1AHwtWuHmaYwxtkBwwGeMsQWiVAP+fbN9AhqZL9cB8LXMRfPlOgC+Fk2UZA6fMcZY7kp1hM8YYyxHHPDnGSJaR0SXERFvKjpHENE5RHQlEVln+1zYlIX4t6J5wCeiSiLaSUS7iehPRGQhop8R0V4iujPhuJQ99oloPRE9keV7rCGiR5Ju20ZE/6ni/D5KRN9M+Pp2Inoh1unzwlK5FiK6JnYee4no0/JaAHwLSnfTn5f4tbwz9nN5hYjeOZvXQUTnEdGLRPRc4u9OisdVxY55kYiul9cG4F4AOwA8lnR8qV3LhUT0bOxncnupXEvs2Gm/h+n+VkrwOlL+naQlhND0A8DfANgR+/xeAJ8A8IvY1z+B0litGsAuAK8nPZYAPAHgmQzPvwLAXxKPgdKe+Sn5fTI89mYAewF8K+G2l2P/tgL4Swldy28AlAOwADgRu+0fARhjn79Z4tfyXOxre+L5zNJ1/P8A6mOfHwJQmeaxPwJwKwAjlA6yBOAL8ngA7QCsJXwt/wNgUey2w3Pg90vttcz4PUSav5USvI6UfyfpPjQf4QshfiKE2B37sg7AxwA8GPv6KQCXIn2P/U9B6cmTyTiA9yXd1g3g0ypOrx3A/5t0W5SIFgG4AEBn4h1z+VqEEB8TQvgBOAB4Y7d9F4CDiL4C4MlSvpbY860EsBHAydm8DiHEZ4QQA0RkhtKOxJ/msZcDeEgIEQHwNoBlQuk5FSSijwA4KYQIlOq1ABgGsBbAciStFJ3j1zLj9zDd30qpXQfS/J2kU7Q9bYnoYiivhKcA9MZuHgOwUggxFjsm8XgXlP/ca2MfiL3tqUx42geEEPclP1YI0UtEyxKeazmSUhoA/h8hxKtEtCLp9l0APgOgDcoreMlcS+zz7wD4t4T7lgO4CcCfS/xaHoEywnQB+P1sXkeCvwXwAAATEe1Ouu9uAGEhhHzBGgPQAOWPsAHA+wF0pXrSErqWR6C8Sw5BGe2XxLUIIR5N/D1MkPZvpYSuI+PfSbKiBHwiqgHwYyivZH8LoCx2lwPp5w2+C+DrQoiQ/M8QQrw7n+8vhDgJYLuK82yD8vbp74jIAOXt1JqkY+bstRDRzQBqhRC/TDh+PxHtAPAWgHtK8VqIyAngCiHEh2P3tRPRThHbc2E2roOItgC4AcDVQohQqusgom8kfBk/FyHEKQDvJaLniahRCNGX8JhSupbPCiFujN3/KBH9VQjRmfCYOXkt6aT7WymV68j2d5JKMSZtLVDeAn1dCHEawD4ob4MAYBOUV8xUtgH4HhE9A+BcIrpL63NLoQzAOlJm6TdA+YHGzeVrIaILAHwNwG0Jt71Ayh7EVgCBpONL6VqMUH4uViJqgZJOCM/WdcRGVT8B8JHYH2M6h4hI9kjZCOA0ET1CRCtjAwobAF/C85bUtUDZza6KiKoArAMQX8Qzx68l1WNT/q2U2HWk/TtJK1uSP9cPAJ8D4AHwTOzjkwAOQHmbeBgJExJIM7mR7vZMx8Qu9hcqHrcd0ydt742d71kAHy6VawHwSuwc5LlVQhkh7APwAoAbS/xa7gQwCCVv/HezeR1Q3iqfTPieq9I85sLYudyHWAFA7LZXAbwI4PbZ/pkUeC23Q0lvjEJJMZTEtaT6PUSav5USvI6UfyfpPnRZaRt7Jd0B4DmR8Ha2FPG1zD1z6TqIaCWAcwH8WSRM0ObweL6WOWa+XAcAbq3AGGMLBa+0ZYyxBYIDPmOMLRAc8BljbIHggM8WJCL6FhFtT3PfuUR0rq4nxJgOOOAzNtO5sQ/G5pWitVZgbK6Jldf9AcqCFQLQTkSPQVkQdVoI8Ski+hco7QNARB8XQlxFROUAfgWgHkqjrc/PzhUwVhge4bOF5A4oi4iugNIPpgnA/wFwPYBlRNQghPg6lGXy3xVCXJXwuA4hxOUAmoho4yycO2MF44DPFpLlAA7GPm+HEvQ/DeB+ADWY6pmSbBWAm2PL5s8B0Fzc02SsODjgs4XkNJT2voCSo78dwEMAPoyEHjcAJqD05wcpnbCOArhHCLEdylL2lF0vGZvreKUtWzCIqBZKDp8AmAE8DuCDUHqnGAH8gxDixVi3xAehjPi/DqXnys8BNEJpkfsREWuRy1gp4YDPGGMLBKd0GGNsgeCAzxhjCwQHfMYYWyA44DPG2ALBAZ8xxhYIDviMMbZA/F+0ZPcYlvRDCAAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#每个付费用户的平均付费额度（ARPPU）\n",
    "\n",
    "data_use_buy1=data[data.behavior_type==4].groupby(['date','user_id'])['behavior_type'].count().reset_index().rename(columns={'behavior_type':'total'})\n",
    "data_use_buy1.groupby('date').apply(lambda x:x.total.sum()/x.total.count()).plot()\n",
    "plt.title('daily_ARPPU')\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'daily_ARPU')"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 活跃用户数平均消费次数=消费总次数/活跃用户人数(每天有操作行为的为活跃) ARPU\n",
    "data['operation']=1\n",
    "data_use_buy2=data.groupby(['date','user_id','behavior_type'])['operation'].count().reset_index().rename(columns={'operation':'total'})\n",
    "data_use_buy2.groupby('date').apply(lambda x:x[x.behavior_type==4].total.sum()/len(x.user_id.unique())).plot()\n",
    "plt.title('daily_ARPU')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'daily_afford_rate')"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#付费率 （消费人数/活跃用户人数）\n",
    "data_use_buy2.groupby('date').apply(lambda x:x[x.behavior_type==4].total.count()/len(x.user_id.unique())).plot()\n",
    "plt.title('daily_afford_rate')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "复购率: 0.8985\n"
     ]
    }
   ],
   "source": [
    "\n",
    "#复购率\n",
    "date_rebuy=data[data.behavior_type==4].groupby('user_id')['date'].apply(lambda x:len(x.unique())).rename('rebuy_count')\n",
    "print('复购率:',round(date_rebuy[date_rebuy>=2].count()/date_rebuy.count(),4))"
   ]
  }
 ],
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